Career Opportunities and Pay

After getting through with DA-100 exam and earning the Microsoft Certified: Data Analyst Associate certification, you will be able to offer more for big business companies that need more analytical power that Excel cannot provide. This opens up multiple job opportunities with decent average annual salaries. Below are some of them as covered by Payscale:

Data Analyst: $61k;
IT Operation Analyst: $56k;
Web Data Analyst: $67k.

Certification Opportunities

Upon completion of this single exam and obtaining the certification, the path doesn’t end. The candidates can pursue other Microsoft certificates to expand their competence area. These include the options such as Microsoft Certified: Azure Data Engineer Associate and Microsoft Certified: Azure Data Scientist Associate, to name a few.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/da-100

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Certification Path

After acquiring the Microsoft Certified: Data Analyst Associate certification, you are competent to go further and broaden your expertise in the Microsoft BI platform. Although this certificate is not a direct requirement for other BI-related validations, it will sure help you get started with the higher-level certifications like the Microsoft Certified: Dynamics 365 + Power Platform Solution Architect Expert.

Microsoft DA-100 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Visualize the data	25%	- Create reports 1. Apply slicing and filtering 2. Format and configure visualizations 3. Choose an appropriate visualization type 4. Import a custom visual 5. Configure conditional formatting 6. Add visualization items to reports 7. Create and manage bookmarks - Enforce accessibility 1. Configure tab order 2. Use accessibility features 3. Design accessible reports - Create dashboards 1. Manage tiles on a dashboard 2. Configure data alerts 3. Set mobile view 4. Use the Q&A feature
Topic 2: Prepare the data	20%	- Get data from different data sources 1. Select a storage mode 2. Identify and connect to a data source 3. Choose an appropriate Power BI data source 4. Select a shared dataset or create a local dataset 5. Change data source settings - Profile the data 1. Examine data structures 2. Interpret data distribution and variance 3. Identify data anomalies - Transform and load the data 1. Design a star schema 2. Create and transform columns 3. Select appropriate column data types 4. Create and transform tables 5. Define relationship cardinality and cross-filter direction - Clean the data 1. Resolve data import errors 2. Resolve inconsistencies, unexpected or null values, and data quality issues 3. Evaluate data, including data statistics and column properties
Topic 3: Model the data	30%	- Create measures by using DAX 1. Create semi-additive measures 2. Create calculated measures 3. Use DAX aggregation functions 4. Use DAX logical functions 5. Implement Time Intelligence using DAX - Design a data model 1. Define quick measures 2. Define a relationship's cross-filter direction and security filtering 3. Design and implement role-playing dimensions 4. Define the tables 5. Configure table and column properties - Optimize model performance 1. Improve performance by identifying and removing unnecessary rows and columns 2. Improve performance by choosing optimal data types 3. Optimize Power Query transformations - Develop a data model 1. Create calculated columns 2. Create calculated tables 3. Implement row-level security roles 4. Create hierarchies
Topic 4: Analyze the data	15%	- Enhance reports for usability and storytelling 1. Create custom tooltips 2. Configure bookmarks 3. Apply sorting 4. Configure sync slicers 5. Group and layer visuals 6. Configure navigation for a report 7. Edit and configure interactions between visuals - Perform advanced analysis 1. Identify outliers 2. Perform What-if analysis 3. Use the Analyze feature 4. Use advanced analytical custom visuals
Topic 5: Deploy and maintain deliverables	10%	- Create and manage workspaces 1. Assign workspace roles 2. Create and configure a workspace 3. Configure and update a workspace app - Manage datasets 1. Configure a dataset scheduled refresh 2. Configure cross-workspace sharing 3. Provide access to datasets 4. Configure row-level security group membership